Data Visualization, Ethics, and Fourth Wing – A Course Review

Recently, I had the wonderful opportunity to enhance my skills in the field of data visualization. It gave me the chance to delve deeper into this subject. I am beyond excited to reveal some incredibly valuable takeaways.

The Data Mindset

With data, it is really the story that matters and not the complexity of charts.

Finding data proxy
It is crucial for researchers to understand the importance of finding data proxy. These proxies serve as substitutes for the information that researchers require without having direct access to the original source. Of course, always use original data, however, sometimes you just need to find a compromise.

Predictive models
When working with quantitative data, it is highly recommended to construct predictive models. Through these models, researchers can make predictions and forecasts based on the available data. These models provide a solid foundation for decision-making and can help convince stakeholders of the validity and reliability of the research findings.

Be versed in many types of data
To excel in the field of research, it is essential to be well-versed in various types of data. Researchers should be knowledgeable and proficient in handling different data sets, whether it be numerical, categorical, or textual. This diverse expertise allows researchers to adapt to a wide range of research contexts and challenges.

Use objective and subjective data
By following these principles and staying updated with the latest methodologies, researchers can ensure that their work is rigorous, comprehensive, and impactful.

Data Visualization

Data visualization is an act of illumination, discovery and recording -the hallmarks of human progress.

By visualizing data, we are exploring it. It is an act of balancing the right information by making important things visually distinguishable, e.g. through visual hierarchy (color palette, font size, placement etc.). It is very helpful to use a limited or a consistent color palette, high contrast, avoiding red and green together, using footnotes to highlight important vs. less important data, do not use too many details. In short, have a good sense of graphic design basics.

Some things to consider while managing trade-offs

1. What message am I trying to convey? (Am I suggesting this item/finding is a problem or not?)
2. To what audience am I conveying this?
3. What are the limitations placed on me by the data I am working with?

The visual representations of data tell a vivid and captivating story about the world we live in. It is essential to have a keen understanding of narrative techniques and the principles of ethical data usage. Inevitably, there will be difficult decisions and compromises that need to be made in this process. However, navigating these trade-offs is crucial in effectively presenting information through the power of graphs and charts.

Narration in Data & Ethics

Moreover, acknowledging the importance of data ethics in our research allows us to develop a deeper understanding of the implications of our findings. Summarizing, here are five points I have found most interesting during this course:

1. Avoiding premature enumeration aka dig deeper:
It is crucial to resist the urge to jump to conclusions based on limited data. Instead, we should strive to delve deeper into our research, analyzing various perspectives and considering all relevant factors.

2. Scrutinize the source aka is the source legitimate:
Evaluating the credibility of our data sources is paramount. By critically examining the legitimacy of the sources, we can ensure the accuracy and reliability of our research.

3. People in the data aka who is missing from the data, who it fails:
Understanding the individuals or groups that are absent from our data is vital. Recognizing such gaps allows us to identify any biases or limitations that may exist, enabling us to address and rectify them.

4. Beware of scamming aka if the data is too good to be true, it probably is:
It is important to exercise caution when encountering data that appears overly favorable or exceptional. Being skeptical and questioning such data helps us maintain a level-headed and objective approach to our research.

5. Error checks aka are you sure your excel has the right equation:
Double-checking and verifying the accuracy of our calculations and data entries is crucial. By conducting thorough error checks, we can ensure the reliability and integrity of our research findings.

6. Consider historical context aka what events or trends may have influenced the data: Contextualizing our data within historical events and trends helps us gain a comprehensive understanding of the factors that may have influenced the outcomes.

7. Ethical implications aka how our research may impact individuals or society:
Reflecting on the ethical implications and potential consequences of our research ensures that we consider the well-being and rights of those affected. This allows us to make informed and responsible decisions.

8. Transparency and accountability aka openness about our research process:
Practicing transparency and being accountable for our research methodologies and findings fosters trust and credibility within the academic community and society at large.

Summary

I enjoyed this course very much. However, it is on a pricey side, so I do not want to name it really. Therefore, what I can recommend to you is learning basics of graphic design, such as layout, fonts, and color theory. The best ones are available on youtube, such as this one.

You will need to practice your visualization skills. I recommend to do that whenever you can. Here is one of my examples of playing with Google Trends data about my current favorite read Fourth Wings by Rebecca Yarros.

And as for the data mindset? I trust you are an ethical human being and already have that covered.

Infographic and playing with data: